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International Conference on Information Management and Technology (ICIMTech)

作者： Bharuno Mahesworo Arif Budiarto Alam Ahmad Hidayat Haryono Soeparno Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Having good sleep is important to maintain physical and mental health. However, many young adults suffer poor sleep due to work or academic demands. Even more, sleep is associated with stress which is many young adults experienced it. To solve this problem, many epidemiologic studies suggest that exercise may improve sleep quality. On the other hand, several studies show that daily activity has no association with sleep quality. In this study, we tried to find more evidence of whether the daily activity has an association with sleep quality or not. We used a commercially available wearable device to capture the subject's heart rate, step count and deep sleep duration for 7 months. Then we used linear regression, XGBoost, and Long Short-Term Memory to find an association between these variables. The results show that there was no association between these variables.

关键词： Sleep Heart rate Biomedical monitoring Computer science Predictive models bioinformatics Data science

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Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States

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The Innovation 2020年第3期1卷 114-122页

作者： Donghai Liang Liuhua Shi Jingxuan Zhao Pengfei Liu Jeremy A.Sarnat Song Gao Joel Schwartz Yang Liu Stefanie T.Ebelt Noah Scovronick Howard H.Chang Gangarosa Department of Environmental Health Rollins School of Public HealthEmory University1518 Clifton Road NEAtlantaGA 30322USA Surveillance and Health Services Research Program American Cancer SocietyAtlantaGAUSA School of Earth and Atmospheric Sciences Georgia Institute of TechnologyAtlantaGAUSA GeoDS Lab Department of GeographyUniversity of Wisconsin-MadisonMadisonWIUSA Department of Environmental Health Harvard T.H.Chan School of Public HealthBostonMAUSA Department of Biostatistics and Bioinformatics Rollins School of Public HealthEmory UniversityAtlantaGAUSA

BACKGROUND The novel human coronavirus disease 2019(COVID-19)pandemic has claimed more than 600,000 lives worldwide,causing tremendous public health,social,and economic *** the risk factors of COVID-19 are still under investigation,environmental factors,such as urban air pollution,may play an important role in increasing population susceptibility to COVID-19 *** We conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between longterm(2010–2016)county-level exposures to NO2,PM2.5,and O3 and county-level COVID-19 case-fatality and mortality rates in the United *** used both single-and multi-pollutant models and controlled for spatial trends and a comprehensive set of potential confounders,including state-level test positive rate,county-level health care capacity,phase of epidemic,population mobility,population density,sociodemographics,socioeconomic status,race and ethnicity,behavioral risk factors,and *** From January 22,2020,to July 17,2020,3,659,828 COVID-19 cases and 138,552 deaths were reported in 3,076 US counties,with an overall observed case-fatality rate of 3.8%.County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-,bi-,and tri-pollutant *** adjusted for co-pollutants,per interquartile-range(IQR)increase in NO2(4.6 ppb),COVID-19 case-fatality rate and mortality rate were associated with an increase of 11.3%(95%CI 4.9%–18.2%)and 16.2%(95%CI 8.7%–24.0%),*** did not observe significant associations between COVID-19 case-fatality rate and long-term exposure to PM2.5 or O3,although per IQR increase in PM2.5(2.6 mg/m3)was marginally associated,with a 14.9%(95%CI 0.0%–31.9%)increase in COVID-19 mortality rate when adjusted for *** Long-term exposure to NO2,which largely arises from urban combustion sources such as traffic,may enhanc

关键词： AIR POLLUTION NITROGEN DIOXIDE COVID-19 CASEFATALITY RATE MORTALITY

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Employing best input SVR robust lost function with nature-inspired metaheuristics in wind speed energy forecasting

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2020年第3期47卷 572-584页

作者： Caraka, Rezzy Eko Chen, Rung Ching Bakar, Sakhinah Abu Tahmid, Muhammad Toharudin, Toni Pardamean, Bens Huang, Su-Wen College of Informatics Chaoyang University of Technology Taichung City41349 Taiwan School of Mathematical Sciences The National University of Malaysia Bandar Baru Bangi Selangor43600 Malaysia Bioinformatics and Data Science Research Center Bina Nusantara University 11480 Indonesia Manado North Sulawesi91594 Indonesia Department of Statistics Padjadjaran University Jatinagor west java45363 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University and Computer Science Dept. BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Taichung Veterans General Hospital Taiwan

Wind power has been experiencing a quick improvement. Without a doubt, wind is a variable asset that is hard to forecast. For instance, traditionally time series, extra holds are distributed to deal with this uncertainty. This paper presents a comparison of the performance of various Support Vector Regression (SVR) applied to short-term wind power forecasting. The analogy with BORUTA and multivariate adaptive regression splines (MARS) as judge best input and employ genetic algorithm and particle swarm optimization to find best parameter in Support Vector Regression with robust lost function. We measure the accuracy of this models by Symmetric means absolute percentage error (sMAPE) and we get the best model BORUTA-SVR-PSO with sMAPE 2.07155%. Moreover, we measure the energy conversion using Feedback Linearization Control (FLC). © International Association of Engineers.

关键词： Genetic algorithms

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Vertex-Frequency Clustering

Vertex-Frequency Clustering

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IEEE Data Science Workshop (DSW)

作者： Daniel B. Burkhardt Jay S. Stanley III Guy Wolf Smita Krishnaswamy Department of Genetics Computational Biology and Bioinformatics Program Department of Mathematics and Statistics Université de Montréal

We propose a novel approach for clustering the vertices of a graph. The method, Vertex-Frequency Clustering (VFC), considers the local harmonic content of one or many graph signals, forming partitions based on spectral features in the input signal. The method can be related to spectral clustering, and the length scale over which frequencies are considered is tunable. This allows one to cluster data based on intrinsic graph geometry in the context of signal dynamics. VFC is useful for unravelling active regions in a signal, collecting sets of similar observations, or detecting anomalies. We demonstrate the utility of VFC in synthetic and biological data, and show how VFC can be used to identify observations with similar feature sets and signal profiles.

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Categorization and analysis of 14 computational methods for estimating cell potency from single-cell RNA-seq data

arXiv

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arXiv 2023年

作者： Wang, Qingyang Zhai, Zhiqian Lian, Qiuyu Song, Dongyuan Li, Jingyi Jessica Department of Statistics and Data Science University of California Los AngelesCA90095-1554 United States Wellcome Trust Cancer Research UK Gurdon Institute University of Cambridge Cambridgeshire CambridgeCB2 1QN United Kingdom Bioinformatics Interdepartmental Ph.D. Program University of California Los AngelesCA90095-7246 United States Department of Human Genetics University of California Los AngelesCA90095-7088 United States Department of Computational Medicine University of California Los AngelesCA90095-1766 United States Department of Biostatistics University of California Los AngelesCA90095-1772 United States Radcliffe Institute for Advanced Study Harvard University CambridgeMA02138 United States

In single-cell RNA sequencing (scRNA-seq) data analysis, a critical challenge is to infer hidden cellular dynamic processes from measured static cell snapshots. To tackle this challenge, many computational methods have been developed from distinct perspectives. Besides the common perspectives of inferring pseudotime trajectories and RNA velocities, another important perspective is to estimate the differentiation potential of cells, which is commonly referred to as the "cell potency." In this review, we provide a comprehensive summary of 14 computational methods that define cell potency from scRNA-seq data under different assumptions, some of which are even conceptually contradictory. We divide these methods into three categories: average-based, entropy-based, and correlation-based methods, depending on how a method summarizes gene expression levels of a cell or cell type into a potency measure. Our review focuses on the key similarities and differences of the methods within each category and between the categories, providing a high-level intuition for each method. Moreover, we use a unified set of mathematical notations to detail the 14 methods’ methodologies and summarize their usage complexities, including the number of parameters, the number of required inputs, and the changes from the method description in publications to the method implementation in software packages. In conclusion, we regard cell potency estimation as an open question that lacks a consensus on the optimal approach, calling for benchmark datasets and studies. Through categorization and detailed description of existing methods, we aim to provide a solid foundation for future benchmark studies of cell potency estimation methods. A broader open challenge is to understand the comparative advantages of methods that infer cellular dynamics from scRNA-seq data using diverse perspectives, including pseudotime trajectories, RNA velocities, and cell potency. © 2023, CC BY-NC-ND.

关键词： Gene expression

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An obstetric brachial plexus lesion rehabilitation platform

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Research on Biomedical Engineering 2019年第2期35卷 167-172页

作者： Alberti, Eduardo Juliano Pichorim, Sérgio Francisco Brawerman, Alessandro Curitiba Paraná80230-901 Brazil Computer Engineering School Coordenação de Engenharia da Computação Positivo University Bloco Vermelho Sala 217 Rua Professor Pedro Viriato Parigot de Souza 5300 – Campo Comprido CuritibaParaná Brazil Bioinformatics Graduate Program Federal University of Paraná CuritibaParaná Brazil

Purpose: Obstetric brachial plexus lesions (OBPL) are caused by the lesion or rupture of the cervical and thoracic nerves during birth. Physical therapy, based on ludic activities, can be useful to improve the OBPL treatment in children. This paper proposes a rehabilitation platform with a ludic interface (lights and sounds), using the magnitude motion gain of a user to aid in the OBPL treatment. Methods: The motor development table (MDT) is an electronic platform composed of eight light segments (with green and red LEDs) that detect the touch of a child’s hand (by optic proximity sensors). Each touch generates a different sound, depending on the exercise. The physiotherapist can choose the MDT game, and the child score can be recorded. The operation of the rehabilitation platform was tested in relation to its behavior depending on the environmental lighting, its efficiency in data processing, and its maximum distance of drive. We also applied an opinion survey. Results: The tests showed that the MDT can be used in environments with up to 1015 lx of illumination and that the incidence of high-intensity light affects the segments’ ability to detect the hand. In addition, the tests demonstrated that the behavior of this device is not affected by the number of errors or triggers performed during the exercises. Conclusion: Based on these findings and on the opinion survey, it is possible to conclude that the MDT can reliably assist the physiotherapist in orthopedic management by providing feedback from the sessions and the patients’ temporal progress. © 2019, Sociedade Brasileira de Engenharia Biomedica.

关键词： Digital storage

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Hopper flows of deformable particles

arXiv

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arXiv 2022年

作者： Cheng, Yuxuan Treado, John D. Lonial, Ben Habdas, Piotr Weeks, Eric R. Shattuck, Mark D. O'Hern, Corey S. Department of Physics Yale University New HavenCT06520 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Physics Emory University AtlantaGA30322 United States Department of Physics Saint Joseph's University PhiladelphiaPA19131 United States Benjamin Levich Institute Physics Department The City College of New York New YorkNY10031 United States Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

Numerous experimental and computational studies show that continuous hopper flows of granular materials obey the Beverloo equation that relates the volume flow rate Q and the orifice width w: Q ∼ (w/σavg − k)β, where σavg is the average particle diameter, kσavg is an offset where Q ∼ 0, the power-law scaling exponent β = d − 1/2, and d is the spatial dimension. Recent studies of hopper flows of deformable particles in different background fluids suggest that the particle stiffness and dissipation mechanism can also strongly affect the power-law scaling exponent β. We carry out computational studies of hopper flows of deformable particles with both kinetic friction and background fluid dissipation in two and three dimensions. We show that the exponent β varies continuously with the ratio of the viscous drag to the kinetic friction coefficient, λ = ζ/µ. β = d−1/2 in the λ → 0 limit and d− 3/2 in the λ → ∞ limit, with a midpoint λc that depends on the hopper opening angle θw. We also characterize the spatial structure of the flows and associate changes in spatial structure of the hopper flows to changes in the exponent β. The offset k increases with particle stiffness until k ∼ kmax in the hard-particle limit, where kmax ∼ 3.5 is larger for λ → ∞ compared to that for λ → 0. Finally, we show that the simulations of hopper flows of deformable particles in the λ → ∞ limit recapitulate the experimental results for quasi-2D hopper flows of oil droplets in water. © 2022, CC BY.

关键词： Stiffness

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利用中心原子价层轨道阐释软硬酸碱理论的原理与应用

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化学教育（中英文） 2024年第6期45卷 99-107页

作者：杨雪梅王志鹏张永臻马新雨 Chen Maggie 蒋振雄哈尔滨工业大学(深圳)理学院广东深圳518055 Division of Genetics Department of MedicineBrigham and Women’s HospitalDepartment of Biological Chemistry and Molecular PharmacologyHarvard Medical SchoolBostonMA02115USA Department of Chemistry Texas A&M UniversityCollege StationTX77840USA 清华大学化学系北京100084 澳门科技大学创新工程学院材料科学与工程系中国澳门999078 Department of Chemistry and Chemical Biology Harvard UniversityBostonMA02138USA Department of Microbiology Miami UniversityOxfordOH45056USA Computational Biology and Bioinformatics Program Duke UniversityDurhamNC27703USA

软硬酸碱理论作为基础化学的重要理论,其在教学与教材中却存在定义不清、难以应用、适用范围不明、模棱两可等众多问题。借用前线轨道理论的观念,针对核心原子的外层轨道进行系统性讨论,并分类举例说明其适用范围与应用方式,以期对基础... 详细信息

软硬酸碱理论作为基础化学的重要理论,其在教学与教材中却存在定义不清、难以应用、适用范围不明、模棱两可等众多问题。借用前线轨道理论的观念,针对核心原子的外层轨道进行系统性讨论,并分类举例说明其适用范围与应用方式,以期对基础教学和相关科研有助。

关键词：软硬酸碱理论前线轨道理论亲核进攻电负性

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Comparison of Performance between Machine Learning Technique and Logistic Regression in Terms of Risk Prediction for Malignancy of the Intraductal Papillary Mucinous Neoplasm of Pancreas

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HPB 2021年 23卷 S51-S51页

作者： Kang, J.S. Lee, C. Han, Y. Choi, Y.J. Byun, Y. Kim, H. Kwon, W. Park, T. Jang, J.-Y. Surgery and Cancer Research Institute Seoul National University College of Medicine Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National University Republic of Korea

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In silico search reveals the association of lichens with black yeast-like fungi in the order Chaetothyriales

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Fungal Biology 2025年

作者： Flavia de Fatima Costa Bruno Paulo Rodrigues Lustosa Camila Pereira Perico Ricardo Belmonte-Lopes João Lucas Vitório Ribeiro Carvalho Emanuel L. Razzolini Germana Davila dos Santos Bruna Jacomel Favoreto de Souza Lima Cristina Maria de Souza Motta Roberto Tadeu Raittz Yinggai Song Laura Selbmann G. Sybren de Hoog Jacques Meis Vania Aparecida Vicente Engineering Bioprocess and Biotechnology Post-Graduation Program Department of Bioprocess Engineering and Biotechnology Federal University of Parana Curitiba Paraná Brazil Graduate Program in Bioinformatics SEPT Federal University of Paraná Curitiba Paraná Brazil Laboratory of Artificial Intelligence Applied to Bioinformatics SEPT Federal University of Paraná Curitiba Paraná Brazil Department of Ecological and Biological Sciences Tuscia University 01100 Viterbo Italy Center of Expertise in Mycology of Radboud University Medical Center / Canisius Wilhelmina Hospital Nijmegen The Netherlands Department of Mycology Federal university of Pernambuco Recife Brazil Department of Dermatology Peking University First Hospital Peking University Beijing China Italian National Antarctic Museum (MNA) Mycological Section 16121 Genoa Italy Institute of Translational Research Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases and Excellence Centre for Medical Mycology University of Cologne Cologne Germany

Lichens exemplify a unique symbiotic relationship between fungi and algae or cyanobacteria, where fungi (mycobionts) provide structural support, while algae or cyanobacteria (photobionts) provide nutrients. Recent discoveries in the order Chaetothyriales have led to the description of several lichenicolous species, underscoring an intricate relationship of some black yeast-like fungi with lichens. The present study aims to investigate public metagenomic data of lichens available in the SRA database, covering a total of 2,888 samples. The analysis incorporated 122 molecular marker sequences (barcodes and padlock probes) previously documented in the literature for species classified within Chaetothyriales. Additionally, 11 novel barcodes for species recently identified in lichens of the genera Cladophialophora and Paracladophialophora are described. The selected metagenomes were then compared with molecular marker sequences using local BLASTn (v2.6.0+), considering only alignments with a coverage cut-off and 100% identity (perfect match). Reads from each sample were retrieved from the SRA as a multifasta file and analyzed with the SWeeP method for vector-based, alignment-free sequence analysis. The analysis identified fungi that are known as environmental inhabitants and, occasionally, opportunistic pathogens of vertebrates, including species in the genera Cladophialophora , Cyphellophora , and Exophiala . These species were distributed across 11 BioProjects from various locations around the world. The findings of this study corroborate extant knowledge concerning fungal colonization in diverse extremophilic environments, including deserts, tundra, and rocky surfaces.

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